After reading the Start-up Expert's first book 'Get Ready' you will have a better understanding of the challenges ahead and whether you have the character and determination to succeed. You will be reassured that qualifications are irrelevant and read stories about those who succeed against all odds. The book is designed to serve as encouragement and inspiration, while at the same time providing practical advice.Alistair Milne is a serial entrepreneur and investor who already has 16 years of hands on start-up experience at age 33. Alistair has started more than 6 businesses since founding his first limited company at 17 and he has invested in many more. He moved to Monaco aged just 25 and his businesses currently employ well over 250 people.Alistair has no degree in business studies or MBA, everything he knows about start-ups has been learned the hard way through running actual businesses from start to exit. He is truly a 'Start-up Expert'.

    However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice-freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You'll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you've mastered these techniques, you'll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes - Learning the Bayesian "state of mind" and its practical implications - Understanding how computers perform Bayesian inference - Using the PyMC Python library to program Bayesian analyses - Building and debugging models with PyMC - Testing your model's "goodness of fit" - Opening the "black box" of the Markov Chain Monte Carlo algorithm to see how and why it works - Leveraging the power of the "Law of Large Numbers" - Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning - Using loss functions to measure an estimate's weaknesses based on your goals and desired outcomes - Selecting appropriate priors and understanding how their influence changes with dataset size - Overcoming the "exploration versus exploitation" dilemma: deciding when "pretty good" is good enough - Using Bayesian inference to improve A/B testing - Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.

    

    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

    Ten Illustrated Essays About Scrubs

    Data Governance should not be about command-and-control, yet at times could become invasive or threatening to the work, people and culture of an organization. Non-Invasive Data Governance™ focuses on formalizing existing accountability for the management of data and improving formal communications, protection, and quality efforts through effective stewarding of data resources. Non-Invasive Data Governance will provide you with a complete set of tools to help you deliver a successful data governance program. Learn how: Steward responsibilities can be identified and recognized, formalized, and engaged according to their existing responsibility rather than being assigned or handed to people as more work. Governance of information can be applied to existing policies, standard operating procedures, practices, and methodologies, rather than being introduced or emphasized as new processes or methods. Governance of information can support all data integration, risk management, business intelligence and master data management activities rather than imposing inconsistent rigor to these initiatives. A practical and non-threatening approach can be applied to governing information and promoting stewardship of data as a cross-organization asset. Best practices and key concepts of this non-threatening approach can be communicated effectively to leverage strengths and address opportunities to improve.

    As tiny and inconspicuous as it may seem, That-Which-Had-Been exhibits an unexpected and varied gift for survival, as it journeys implacably toward its ultimate destination. Along the way, it meets a rich array of ordinary human beings, some of whom assist it along its way, others who impede its progress, none of whom have any idea of its existence.From whence comes the strange, but universal, experience of deja vu? Why do some people exhibit a wisdom far beyond their age and experience - persons reincarnationists refer to as 'old souls'? Joseph Wurtenbaugh in this short story offers a fascinating and tantalizingly plausible explanation for these phenomena, presented in a natural setting that brims with adventure and exhilarating possibility. Not to be missed by anyone who enjoys science fiction or thinking outside the box.

    The chafing restrictions of a typical upbringing in upper-class, small town Alabama simply did not apply to Zelda, who was described as an unusual child and permitted to roam the streets with little supervision. Zelda refused to blossom into a typical 'Southern belle' on anyone's terms but her own and while still in high school enjoyed the status of a local celebrity for her shocking behavior. Everybody in town knew the name Zelda Sayre. Queen of the Montgomery social scene, Zelda had a different beau ready and willing to show her a good time for every day of the week. Before meeting F. Scott Fitzgerald, Zelda's life was a constant pursuit of pleasure. With little thought for the future and no responsibilities to speak of, Zelda committed herself fully to the mantra that accompanied her photo in her high school graduation book: "Why should all life be work, when we all can borrow. Let's think only of today, and not worry about tomorrow." But for now Zelda was still in rehearsal for her real life to begin, a life she was sure would be absolutely extraordinary. Zelda Sayre married F. Scott Fitzgerald on the 3rd of April 1920 and left sleepy Montgomery behind in order to dive headfirst into the shimmering, glamourous life of a New York socialite. With the publication of Scott's first novel, This Side of Paradise, Zelda found herself thrust into the limelight as the very epitome of the Flapper lifestyle. Concerned chiefly with fashion, wild parties and flouting social expectations, Zelda and Scott became icons of the Jazz Age, the personification of beauty and success. What Zelda and Scott shared was a romantic sense of self-importance that assured them that their life of carefree leisure and excess was the only life really worth living. Deeply in love, the Fitzgeralds were like to sides of the same coin, each reflecting the very best and worst of each other. While the world fell in love with the image of the Fitzgeralds they saw on the cover of magazines, behind the scenes the Fitzgerald's marriage could not withstand the tension of their creative arrangement. Zelda was Scott's muse and he mercilessly mined the events of their life for material for his books. Scott claimed Zelda's memories, things she said, experiences she had and even passages from her diary as his possessions and used them to form the basis of his fictional works. Zelda had a child but the domestic sphere offered no comfort or purpose for her. The Flapper lifestyle was not simply a phase she lived through, it formed the very basis of her character and once the parties grew dull, the Fitzgeralds' drinking became destructive and Zelda's beauty began to fade, the world held little allure for her. Zelda sought reprieve in work and tried to build a career as a ballet dancer. When that didn't work out she turned to writing but was forbidden by Scott from using her own life as material. Convinced that she would never leave her mark on the world as deeply or expressively as Scott had, Zelda retreated into herself and withdrew from the people she knew in happier times. The later years of Zelda's life were marred by her detachment from reality as, diagnosed with schizophrenia, Zelda spent the last eighteen years of her life living in and out of psychiatric hospitals. As Scott's life unraveled due to alcohol abuse, Zelda looked back on the years they had spent together, young and wild and beautiful, as the best of her life. She may have been right but she was wrong about one thing, Zelda did leave her mark on the world and it was a deep and expressive mark that no one could have left but her. Zelda Fitzgerald: The Biography

     From the files and pen of world renowned true crime writer Alan Hynd (1903 - 1974) comes the final installment of deliciously dark true murder cases of the first half of the 20th Century. These stories, the third of these three short collections, are unified by a single theme: they all involve physicians. And not for the autopsy, but as perpetrators or accused perpetrators. You may never see your family care giver again in the same light. Told in the characteristic wry, anecdotal reportorial style that made Alan Hynd famous in his day (two wartime best sellers in 1943, contributions to The Reader's Digest, Colliers, Coronet, The Saturday Evening Post, True, Liberty, The American Mercury and almost every true detective magazine in print) these tales will have you cringing one minute, laughing the next, and gasping in shock a moment later. Truly, no one could make up classics like these. We meet here the notorious Dr. Cream, a twitchy-eyed psychotic with a yen for prostitutes, a Philadelphia chiropractor whose girlfriend lost her head, and Marcel Petiot, whose patients payed their own way out of this world. Then as a bonus, get to know (from a safe distance) "Lethal Louise," the black widow of California, and Adolf Luetgert of Chicago, whose sausage-making plant was put to extracurricular uses. This is not for the faint of heart. True crime is always farther out there than fiction.

    Football's data revolution has only just begun. The arrival of advanced metrics and detailed analysis is already reshaping the modern game. We can now fully assess player performance, analyse the role of luck and measure what really leads to victory. There is no turning back.Now the race is on between football's wealthiest clubs and a group of outsiders, nerds and rule-breakers, who are turning the game on its head with their staggering innovations. Winning is no longer just about what happens out on the pitch, it's now a battle taking place in boardrooms and on screens across international borders with the world's brightest minds driving for an edge over their fiercest rivals.Christoph Biermann has moved in the midst of these disruptive upheavals, talking to scientists, coaches, managers, scouts and psychologists in the world's major clubs, traveling across Europe and the US and revealing the hidden - and often jaw-dropping - truths behind the beautiful game. 'A book full of exciting ideas and inside views on modern football. The most exciting book in an exciting time for football.' Thomas Hitzlsperger

    Stern administrators lorded over sterile university laboratories and stressed one point to the wide-eyed students privileged enough to set foot within them: Computers were not toys.Defying authority, hackers seized control of monolithic mainframes to create a new breed of computer game: the roguelike, cryptic and tough-as-nails adventures drawn from text-based symbols instead of state-of-the-art 3D graphics.Despite their visual simplicity, roguelike games captivate thousands of players around the world. From the author of the bestselling Stay Awhile and Listen series, Dungeon Hacks introduces you to the visionaries behind some of the most popular roguelikes of all time, and shows how their creations paved the way for the blockbuster video games of today—and beyond.

    The field is ready for a text that not only demonstrates how to use the algorithms that make up machine learning methods, but also provides the background needed to understand how and why these algorithms work. Machine Learning: An Algorithmic Perspective is that text.Theory Backed up by Practical ExamplesThe book covers neural networks, graphical models, reinforcement learning, evolutionary algorithms, dimensionality reduction methods, and the important area of optimization. It treads the fine line between adequate academic rigor and overwhelming students with equations and mathematical concepts. The author addresses the topics in a practical way while providing complete information and references where other expositions can be found. He includes examples based on widely available datasets and practical and theoretical problems to test understanding and application of the material. The book describes algorithms with code examples backed up by a website that provides working implementations in Python. The author uses data from a variety of applications to demonstrate the methods and includes practical problems for students to solve.Highlights a Range of Disciplines and ApplicationsDrawing from computer science, statistics, mathematics, and engineering, the multidisciplinary nature of machine learning is underscored by its applicability to areas ranging from finance to biology and medicine to physics and chemistry. Written in an easily accessible style, this book bridges the gaps between disciplines, providing the ideal blend of theory and practical, applicable knowledge."

    At first unable to run 400 metres without stopping, Laura has now completed five marathons, the most recent in under four hours. Along the way, Laura learns countless lessons about running, most of them the hard way. But most importantly this self-confessed couch potato learns to love running. As well as offering inspiration and motivation to get out there and run, her book offers tips on how to make running easier and more enjoyable. Offering practical information on buying the right kit, choosing the best race and what to do on race day, it also tackles the important running questions you might be embarrassed to ask – like when will it get easier? And what happens if I need the toilet?

    If your job requires you to manage and analyze all kinds of data, turn to Head First Data Analysis, where you'll quickly learn how to collect and organize data, sort the distractions from the truth, find meaningful patterns, draw conclusions, predict the future, and present your findings to others. Whether you're a product developer researching the market viability of a new product or service, a marketing manager gauging or predicting the effectiveness of a campaign, a salesperson who needs data to support product presentations, or a lone entrepreneur responsible for all of these data-intensive functions and more, the unique approach in Head First Data Analysis is by far the most efficient way to learn what you need to know to convert raw data into a vital business tool. You'll learn how to:Determine which data sources to use for collecting information Assess data quality and distinguish signal from noise Build basic data models to illuminate patterns, and assimilate new information into the models Cope with ambiguous information Design experiments to test hypotheses and draw conclusions Use segmentation to organize your data within discrete market groups Visualize data distributions to reveal new relationships and persuade others Predict the future with sampling and probability models Clean your data to make it useful Communicate the results of your analysis to your audience Using the latest research in cognitive science and learning theory to craft a multi-sensory learning experience, Head First Data Analysis uses a visually rich format designed for the way your brain works, not a text-heavy approach that puts you to sleep.

    Most don’t find true love. Thanks to Data, a Love Story, their odds just got a whole lot better. Data, A Love Story: How I Gamed Online Dating to Meet My Match is a lively, thought-provoking memoir about how one woman “gamed” the world of online dating—and met her eventual husband.